Research suggests inflammation may be just as important as cholesterol as a cause of heart attacks, suggesting different treatments should be considered for prevention.
Analysis By Clare Wilson
Researchers at the School of Cyber Security at Korea University, Seoul, have presented a new covert channel attack named CASPER can leak data from air-gapped computers to a nearby smartphone at a rate of 20bits/sec.
The CASPER attack leverages the internal speakers inside the target computer as the data transmission channel to transmit high-frequency audio that the human ear cannot hear and convey binary or Morse code to a microphone up to 1.5m away.
The receiving microphone can be in a smartphone recording sound inside the attacker’s pocket or a laptop in the same room.
Deep learning has made significant strides in text generation, translation, and completion in recent years. Algorithms trained to predict words from their surrounding context have been instrumental in achieving these advancements. However, despite access to vast amounts of training data, deep language models still need help to perform tasks like long story generation, summarization, coherent dialogue, and information retrieval. These models have been shown to need help capturing syntax and semantic properties, and their linguistic understanding needs to be more superficial. Predictive coding theory suggests that the brain of a human makes predictions over multiple timescales and levels of representation across the cortical hierarchy. Although studies have previously shown evidence of speech predictions in the brain, the nature of predicted representations and their temporal scope remain largely unknown. Recently, researchers analyzed the brain signals of 304 individuals listening to short stories and found that enhancing deep language models with long-range and multi-level predictions improved brain mapping.
The results of this study revealed a hierarchical organization of language predictions in the cortex. These findings align with predictive coding theory, which suggests that the brain makes predictions over multiple levels and timescales of expression. Researchers can bridge the gap between human language processing and deep learning algorithms by incorporating these ideas into deep language models.
The current study evaluated specific hypotheses of predictive coding theory by examining whether cortical hierarchy predicts several levels of representations, spanning multiple timescales, beyond the neighborhood and word-level predictions usually learned in deep language algorithms. Modern deep language models and the brain activity of 304 people listening to spoken tales were compared. It was discovered that the activations of deep language algorithms supplemented with long-range and high-level predictions best describe brain activity.
There’s a new sight to see in the skies over the eastern seaboard of the United States courtesy of Rocket Lab and NASA.
The space startup is beginning to make a habit of launching its Electron rockets from NASA’s Wallops Flight Facility in Virginia. Unlike the majority of space launches in the US that blast off from the far southeastern corner of the country in Florida, some of the nation’s largest population centers have a view of launches from Wallops.
The “Stronger Together” mission is the second launch of the space startup’s Electron rocket from Virginia. Before adding a second launch facility, all of the company’s previous launches were conducted from its primary launch pads in New Zealand over the past couple years.
There is a competition among technology companies to develop a humanoid robot that can perform various tasks, and one particular company, “Figure,” is at the forefront of this race.
A humanoid general-purpose robot is a robot that can mimic human actions and interact with the environment in a human-like way. This type of robot has the potential to perform various tasks, such as cooking, cleaning, and assisting people with disabilities.
Wondering if artificial intelligence will be taking your job anytime soon? We’re sure we speak for a lot of folks when we say: same.
Considering that AI is literally designed to model human capabilities and thus automate human tasks, it’s a fair question — and one that a group of professors from New York University (NYU), Princeton, and the University of Pennsylvania (UPenn) may have just helped to shed a little bit of light on in a new paper, aptly titled “How Will Language Modelers like ChatGPT Affect Occupations and Industries?”
Though the paper has yet to be peer-reviewed, the results are fascinating, not to mention ominous — especially, of course, for the folks most at risk.
A new experiment pulled off the most precise measurement of an electron’s self-generated magnetic field—and the universe’s subatomic model is at stake.
An international team of researchers, including those from the University of Tokyo’s Institute for Solid State Physics, has made a groundbreaking discovery. They have successfully demonstrated the use of a single molecule named fullerene as a switch, similar to a transistor. The team achieved this by employing a precisely calibrated laser pulse, which allowed them to control the path of an incoming electron in a predictable manner.
The switching process enabled by fullerene molecules can be significantly faster than the switches used in microchips, with a speed increase of three to six orders of magnitude, depending on the laser pulses utilized. The use of fullerene switches in a network could result in the creation of a computer with capabilities beyond what is currently achievable with electronic transistors. Additionally, they have the potential to revolutionize microscopic imaging devices by providing unprecedented levels of resolution.
Over 70 years ago, physicists discovered that molecules emit electrons in the presence of electric fields, and later on, certain wavelengths of light. The electron emissions created patterns that enticed curiosity but eluded explanation. But this has changed thanks to a new theoretical analysis, the ramification of which could not only lead to new high-tech applications but also improve our ability to scrutinize the physical world itself.
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Bouncing cosmology from nonlinear dark energy with two cosmological constants.
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